SoroushVahidi/scidocs huggingface dataset:
Practical Implementations of Arithmetic Coding 1
(1992)

We provide a tutorial on arithmetic coding, showing how it provides nearly optimal data compression and how it can be matched with almost any probabilistic model. We indicate the main disadvantage of arithmetic coding, its slowness, and give the basis of a fast, space-e cient, approximate arithmetic coder with only minimal loss of compression e ciency. Our coder is based on the replacement of arithmetic by table lookups coupled with a new deterministic probability estimation scheme. Index terms : Data compression, arithmetic coding, adaptive modeling, analysis of algorithms, data structures, low precision arithmetic. A similar version of this paper appears in Image and Text Compression, James A. Storer, ed., Kluwer Academic Publishers, Norwell, MA, 1992, 85{112. A shortened version of this paper appears in the proceedings of the International Conference on Advances in Communication and Control (COMCON 3), Victoria, British Columbia, Canada, October 16{18, 1991. Support was provided in part by NASA Graduate Student Researchers Program grant NGT{ 50420 and by a National Science Foundation Presidential Young Investigators Award grant with matching funds from IBM. Additional support was provided by a Universities Space Research Association/CESDIS associate membership. Support was provided in part by National Science Foundation Presidential Young Investigator Award CCR{9047466 with matching funds from IBM, by NSF research grant CCR{9007851, by Army Research O ce grant DAAL03{91{G{0035, and by the O ce of Naval Research and the Defense Advanced Research Projects Agency under contract N00014{91{J{4052ARPA Order No. 8225. Additional support was provided by a Universities Space Research Association/CESDIS associate membership.
Emotional Branding and the Strategic Value of the Doppelgänger Brand Image
(2010)

Emotional branding is widely heralded as a key to marketing success. However, little attention has been given to the risks posed by this strategy. This article argues that emotional-branding strategies are conducive to the emergence of a doppelgänger brand image, which is defined as a family of disparaging images and meanings about a brand that circulate throughout popular culture. This article’s thesis is that a doppelgänger brand image can undermine the perceived authenticity of an emotional-branding story and, thus, the identity value that the brand provides to consumers. The authors discuss how the tenets of emotional branding paradoxically encourage the formation and propagation of doppelgänger brand imagery. This article develops the counterintuitive proposition that rather than merely being a threat to be managed, a doppelgänger brand image can actually benefit a brand by providing early warning signs that an emotional-branding story is beginning to lose its cultural resonance. This article demonstrates these ideas through an analysis of the doppelgänger brand image that is beginning to haunt a paragon of emotional branding—Starbucks. The authors conclude with a discussion of how marketing managers can proactively use the insights gained by analyzing a doppelgänger brand image.
A longitudinal study of the social and emotional predictors and consequences of cyber and traditional bullying victimisation
(2015)

Few longitudinal studies have investigated how cyberbullying interacts with traditional bullying among young people, who are increasingly using online environments to seek information, entertainment and to socialise. This study aimed to identify the associations between the relative contribution of cyberbullying victimisation and traditional bullying victimisation on social and emotional antecedents and outcomes among adolescents. Participants were a cohort of 1,504 adolescents from 16 Australian schools followed from age 13 to 15 years. Adolescents experiencing social and emotional difficulties were more likely to be cyberbullied and traditionally bullied, than traditionally bullied only. Those targeted in both ways experienced more harm and stayed away from school more often than those traditionally bullied only. These findings suggest a high coexistence of cyber and traditional bullying behaviours and their antecedents, and higher levels of harm from a combination of these behaviours for adolescents over time. Future research should engage students as co-researchers to enhance school and parent strategies to support adolescents experiencing difficulties, and to reduce the likelihood of both cyber and traditional bullying.
Seeing Stars When There Aren’t Many Stars: Graph-Based Semi-Supervised Learning For Sentiment Categorization
(2006)

We present a graph-based semi-supervised learning algorithm to address the sentiment analysis task of rating inference. Given a set of documents (e.g., movie reviews) and accompanying ratings (e.g., “4 stars”), the task calls for inferring numerical ratings for unlabeled documents based on the perceived sentiment expressed by their text. In particular, we are interested in the situation where labeled data is scarce. We place this task in the semi-supervised setting and demonstrate that considering unlabeled reviews in the learning process can improve ratinginference performance. We do so by creating a graph on both labeled and unlabeled data to encode certain assumptions for this task. We then solve an optimization problem to obtain a smooth rating function over the whole graph. When only limited labeled data is available, this method achieves significantly better predictive accuracy over other methods that ignore the unlabeled examples during training.
CNN-SLAM: Real-Time Dense Monocular SLAM with Learned Depth Prediction
(2017)

Given the recent advances in depth prediction from Convolutional Neural Networks (CNNs), this paper investigates how predicted depth maps from a deep neural network can be deployed for the goal of accurate and dense monocular reconstruction. We propose a method where CNN-predicted dense depth maps are naturally fused together with depth measurements obtained from direct monocular SLAM, based on a scheme that privileges depth prediction in image locations where monocular SLAM approaches tend to fail, e.g. along low-textured regions, and vice-versa. We demonstrate the use of depth prediction to estimate the absolute scale of the reconstruction, hence overcoming one of the major limitations of monocular SLAM. Finally, we propose a framework to efficiently fuse semantic labels, obtained from a single frame, with dense SLAM, so to yield semantically coherent scene reconstruction from a single view. Evaluation results on two benchmark datasets show the robustness and accuracy of our approach.
Development of a one-axis actively regulated bearingless motor with a repulsive type passive magnetic bearing
(2014)

This paper describes a novel one-axis actively regulated bearingless motor with a spinning top-shaped rotor, which is intended for a use as a cooling fan. This motor requires only one set of three-phase winding and thus one three-phase inverter to realize both rotation and magnetic suspension, and thus it is dubbed a single-drive bearingless motor. An axial position of the rotor is actively regulated and radial and tilting motions are passively stabilized by the passive magnetic bearing. Torque and axial suspension force are regulated by q-axis and d-axis currents, respectively. In this paper, the structure and principle, design, and test results of the proposed bearingless motor are presented.
Mutual information and minimum mean-square error in multiuser Gaussian channels
(2015)

1. Introduction Due to the lack of explicit closed form expressions of the mutual information for binary inputs, which were provided only for the BPSK and QPSK for the single input single output (SISO) case, [1], [2], [3], it is of particular importance to address connections between information theory and estimation theory for the multiuser case. Connections between information theory and estimation theory dates back to the work of Duncan, in [4] who showed that for the continuous-time additive white Gaussian noise (AWGN) channel, the filtering minimum mean squared error (causal estimation) is twice the input-output mutual information for any underlying signal distribution. Recently, Guo, Shamai, and Verdu have illuminated intimate connections between information theory and estimation theory in a seminal paper, [1]. In particular, Guo et al. have shown that in the classical problem of information transmission through the conventional AWGN channel, the derivative of the mutual information with respect to the SNR is equal to the smoothing minimum mean squared error (noncausal estimation); a relationship that holds for scalar, vector, discrete-time and continuous-time channels regardless of the input statistics. There have been extensions of these results to the case of mismatched input distributions in the scalar Gaussian channel in [5] and [6]. However, the fundamental relation between the derivative of the mutual information and the MMSE, known as I-MMSE identity, and defined for point to point channels with any noise or input distributions in [1] is not anymore suitable for the multiuser case. Therefore, in this paper, we revisit the connections between the mutual information and the MMSE for the multiuser setup. We generalize the I-MMSE relation to the multiuser case. In particular, we prove that the derivative of the mutual information with respect to the signal to noise ratio (SNR) is equal to the minimum mean squared error (MMSE) plus a covariance induced due to the interference, quantified by a term with respect to the cross correlation of the users inputs' estimates, their channels, and their precoding matrices. Further, we capitalize on this unveiled multiuser I-MMSE relation to derive the components of the multiuser mutual information. In particular, we derive the derivative of the conditinal and non-conditional mutual information with respect to the SNR. Further extensions of this result allows a generalization of the relations of linear vector Gaussian channels in [7] to multiuser channels. In particular, [8], [9] generalize the I-MMSE relation to the per-user gradient …
Mersenne Twister A Pseudo-Random Number Generator
(2007)

Pseudo random number generators have been widely used in numbers of applications, particularly simulation and cryptography. Among them is a Mersenne Twister. Introduced in 1998 by Makoto Matsumoto and Takuji Nishimura, it has been a highly preferred generator since it provides long period, high order of dimensional equidistribution, speed and reliability. In this paper, we will focus mainly on describing the theories and algorithm of the Mersenne Twister. We also briefly introduce its variants and discuss its limitations and improvements.
Evaluating WAP News Sites: The Webqual/m Approach
(2001)

This paper reports on the evaluation of wireless Internet news sites using the WebQual/m instrument. From initial application in the domain of traditional Internet Web sites, the instrument has been adapted for sites delivered using the wireless application protocol (WAP). The WebQual approach is to assess the Web-site quality from the perspective of the 'voice of the customer’, an approach adopted in quality function deployment. The WebQual/m instrument is used to assess customer perceptions of information, site and useroriented qualities. In particular, the qualities of three UK-based WAP news sites are assessed via an online questionnaire. The results are reported and analysed and demonstrate considerable variations in the offerings of the news sites. The findings and their implications for mobile commerce are discussed and some conclusions and directions for further research are provided.
Phialemoniopsis endophytica sp. nov., a new species of endophytic fungi from Luffa cylindrica in Henan, China
(2016)

During a survey of endophytic fungi in the cucurbit plants collected from Henan, China, a new species, Phialemoniopsis endophytica was isolated from the lower stem of Luffa cylindrica. It differs from other Phialemoniopsis species by its cylindrical to flask-shaped phialides, falcate conidia with blunt ends, ostiolate pycnidium-like conidiomata without marginal setae and ellipsoidal chlamydospores. Multi-locus (ITS, LSU, ACT, and TUB) phylogenetic analysis confirmed that P. endophytica is distinct from other species. A synopsis of the morphological characters of the new species is provided.
Learning user interaction models for predicting web search result preferences
(2006)

Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of web search users to predict web search result preferences. Accurate modeling and interpretation of user behavior has important applications to ranking, click spam detection, web search personalization, and other tasks. Our key insight to improving robustness of interpreting implicit feedback is to model query-dependent deviations from the expected "noisy" user behavior. We show that our model of clickthrough interpretation improves prediction accuracy over state-of-the-art clickthrough methods. We generalize our approach to model user behavior beyond clickthrough, which results in higher preference prediction accuracy than models based on clickthrough information alone. We report results of a large-scale experimental evaluation that show substantial improvements over published implicit feedback interpretation methods.
Diffusion dynamics on multiplex networks
(2013)

We study the time scales associated with diffusion processes that take place on multiplex networks, i.e., on a set of networks linked through interconnected layers. To this end, we propose the construction of a supra-laplacian matrix, which consists of a dimensional lifting of the laplacian matrix of each layer of the multiplex network. We use perturbative analysis to reveal analytically the structure of eigenvectors and eigenvalues of the complete network in terms of the spectral properties of the individual layers. The spectrum of the supra-laplacian allows us to understand the physics of diffusionlike processes on top of multiplex networks.
Gender Classification of Blog Authors: With Feature Engineering and Deep Learning using LSTM Networks
(2017)

In this paper, we present two approaches to automatically classify the gender of blog authors: the first is a manual feature extraction based system incorporating two novel feature classes: variable length character sequence patterns and thirteen new word classes, along with an added class of surface features while the second is a first-ever application of a memory variant of Recurrent Neural Networks, i.e. Bidirectional Long Short Term Memory Networks (BLSTMs) on this task. We use two blog data sets to report our results: the first is a well-explored one used by the previous state-of-the-art model while the other is a 20 times larger corpus. For the first system, we use a voting of machine learning classifiers to obtain an improved accuracy with respect to the previous feature mining systems on the former data set. Using our second approach, we show that the accuracy obtained using such deep LSTMs is comparable to the current state-of-the-art deep learning system for the task of gender classification. Finally, we carry out a comparative study of performance of both the systems on the two data sets.
Decision Making Under Uncertainty in Visualisation
(2015)

Decision making under uncertainty can lead to irrational behaviour; such errors are often being referred to as cognitive biases. Related work in this area has tended to focus on the human’s analytic and sensemaking processes. This paper puts forward a novel perspective on this, proposing that some cognitive biases can also occur in the process of viewing visualisations. Consequently, this source of error may have a negative impact on decision making. This paper presents examples of situations where cognitive biases in visualisation can occur and outlines a future user study to investigate the anchoring and adjustment cognitive biases in visualisation.
Detection of SQL injection and XSS attacks in three tier web applications
(2016)

Web applications are used on a large scale worldwide, which handles sensitive personal data of users. With web application that maintains data ranging from as simple as telephone number to as important as bank account information, security is a prime point of concern. With hackers aimed to breakthrough this security using various attacks, we are focusing on SQL injection attacks and XSS attacks. SQL injection attack is very common attack that manipulates the data passing through web application to the database servers through web servers in such a way that it alters or reveals database contents. While Cross Site Scripting (XSS) attacks focuses more on view of the web application and tries to trick users that leads to security breach. We are considering three tier web applications with static and dynamic behavior, for security. Static and dynamic mapping model is created to detect anomalies in the class of SQL Injection and XSS attacks.
The reviewing of object files: Object-specific integration of information
(1992)

A series of experiments explored a form of object-specific priming. In all experiments a preview field containing two or more letters is followed by a target letter that is to be named. The displays are designed to produce a perceptual interpretation of the target as a new state of an object that previously contained one of the primes. The link is produced in different experiments by a shared location, by a shared relative position in a moving pattern, or by successive appearance in the same moving frame. An object-specific advantage is consistently observed: naming is facilitated by a preview of the target, if (and in some cases only if) the two appearances are linked to the same object. The amount and the object specificity of the preview benefit are not affected by extending the preview duration to 1 s, or by extending the temporal gap between fields to 590 ms. The results are interpreted in terms of a reviewing process, which is triggered by the appearance of the target and retrieves just one of the previewed items. In the absence of an object link, the reviewing item is selected at random. We develop the concept of an object file as a temporary episodic representation, within which successive states of an object are linked and integrated.
On computable numbers, with an application to the Entscheidungsproblem
(1937)

The "computable" numbers may be described briefly as the real numbers whose expressions as a decimal are calculable by finite means. Although the subject of this paper is ostensibly the computable numbers. it is almost equally easy to define and investigate computable functions of an integral variable or a real or computable variable, computable predicates, and so forth. The fundamental problems involved are, however, the same in each case, and I have chosen the computable numbers for explicit treatment as involving the least cumbrous technique. I hope shortly to give an account of the relations of the computable numbers, functions, and so forth to one another. This will include a development of the theory of functions of a real variable expressed in terms of computable numbers. According to my definition, a number is computable if its decimal can be written down by a machine.
No Free Lunch Theorems for Search
(1995)

We show that all algorithms that search for an extremum of a cost function perform exactly the same when averaged over all possible cost functions In particular if algorithm A outperforms algorithm B on some cost functions then loosely speaking there must exist exactly as many other functions where B outperforms A Starting from this we analyze a number of the other a priori characteristics of the search problem like its geometry and its information theoretic aspects This analysis allows us to derive mathematical benchmarks for assessing a particular search algo rithm s performance We also investigate minimax aspects of the search problem the validity of using characteristics of a partial search over a cost function to predict future behavior of the search algorithm on that cost function and time varying cost functions We conclude with some discussion of the justi ability of biologically inspired search methods
Information Retrieval from Neurophysiological Signals
(2017)

One of the ultimate goals of neuroscience is decoding someone’s intentions directly from his/her brain activities. In this thesis, we aim at pursuing this goal in different scenarios. Firstly, we show the possibility of creating a user-centric music/movie recommender system by employing neurophysiological signals. Regarding this, we employed a brain decoding paradigm in order to classify the features extracted from brain signals of participants watching movie/music video clips, into our target classes (two broad music genres and four broad movie genres). Our results provide a preliminary experimental evidence towards user-centric music/movie content retrieval by exploiting brain signals. Secondly, we addressed one of the main issue of the applications of brain decoding algorithms. Generally, the performance of such algorithms suffers from the constraint of having few and noisy samples, which is the case in most of the neuroimaging datasets. In order to overcome this limitation, we employed an adaptation paradigm in order to transfer knowledge from another domain (e.g. large-scale image domain) to the brain domain. We experimentally show that such adaptation procedure leads to improved results. We performed such adaptation pipeline on different tasks (i.e. object recognition and genre classification) using different neuroimaging modalities (i.e. fMRI, EEG, and MEG). Thirdly, we aimed at one of the fundamental goals in brain decoding which is reconstructing the external stimuli using only the brain features. Under this scenario, we show the possibility of regressing the stimuli spectrogram using time-frequency analysis of the brain signals. Finally, we conclude the thesis by summarizing our contributions and discussing the future directions and applications of our research.
An energy framework for the network simulator 3 (NS-3)
(2011)

The Network Simulator-3 (ns-3) is rapidly developing into a flexible and easy-to-use tool suitable for wireless network simulation. Since energy consumption is a key issue for wireless devices, wireless network researchers often need to investigate the energy consumption at a battery powered node or in the overall network, while running network simulations. This requires the underlying simulator to support energy consumption and energy source modeling. Currently however, ns-3 does not provide any support for modeling energy consumption or energy sources. In this paper, we introduce an integrated energy framework for ns-3, with models for energy source as well as energy consumption. We present the design and implementation of the overall framework and the specific models therein. Further, we show how the proposed framework can be used in ns-3 to simulate energy-aware protocols in a wireless network.